The applicants? long-term aim is to support the further advancement and clinical translation of computational models of cardiac tissues. Crucial parameters for computational models of tissue electrophysiology are the intra- and extracellular electrical conductivities. Currently, our knowledge about these conductivities originates from a small set of studies performed 40 years ago on ventricular tissue from animal hearts. Conductivities of human, aged and diseased tissues have still not been established. In this study, we will test the hypothesis that a novel computational approach and advanced 3D microelectrode arrays provide a means for accurate measurement of conductivities for modeling of cardiac tissue electrophysiology. Our approach will facilitate the measurement of conductivity tensors that comprehensively describe the anisotropic electrical properties of the extracellular and intracellular domains of biological tissue.
In Specific Aim 1, we will use the computational approach to assess designs of 3D microelectrode arrays and current application protocols. We will vary the spacing of recording electrodes within the degrees of freedom for manufacturing of the microelectrode arrays. We will also investigate protocols and electrode locations for current application. The optimal array and current application protocol will be further assessed in studies on tissue surrogates. In these studies, we hypothesize that the modeling-based approach is capable of accurately measuring the conductivity of both isotropic and anisotropic media. We will determine the accuracy of the conductivity measurements.
In Specific Aim 2, we will explore the utility of the modeling-based approach for measurement of conductivity in living cardiac tissues. Using tissues excised from the left ventricle of rat, we will test the hypothesis that the computational approach provides reliable measures of conductivity of living tissues. We will assess our measurements by comparison with prior studies. Subsequently, we will investigate the feasibility of the approach for conductivity measurements of the left ventricular free wall of the isolated rat heart. We will apply an established model of the isolated rat heart based on retrograde perfusion through the aorta. We will perfuse the hearts with solutions associated with normal, increased and decreased extracellular volume. We hypothesize that extracellular conductivities increase and decrease for the solutions that increase and decrease the extracellular volume, respectively, when compared to control. Together, the proposed studies constitute a crucial step towards establishing the proposed innovative approach for measurement of intra- and extracellular conductivities. Applications of the proposed framework include establishing conductivities of cardiac tissues at different sites of the human and aged heart. Also, application of the framework will facilitate the creation of a library of conductivity measurements for various cardiac diseases, for instance, hypertrophic cardiomyopathy and ventricular fibrosis. We suggest that such a library will have a sustained, powerful impact on computational cardiovascular research and medicine.

Public Health Relevance

Progress in clinical translation of computational modeling for applications in cardiology and cardiac surgery requires comprehensive knowledge on tissue properties in human and in disease. This feasibility study will establish a framework for measurement of electrical tissue properties that are crucial for computational modeling of cardiac conduction. The framework is based on a unique mathematical approach and three- dimensional microelectrode technology.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Small Research Grants (R03)
Project #
1R03EB029625-01
Application #
9957749
Study Section
Electrical Signaling, Ion Transport, and Arrhythmias Study Section (ESTA)
Program Officer
Peng, Grace
Project Start
2020-06-01
Project End
2022-03-31
Budget Start
2020-06-01
Budget End
2021-03-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Utah
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112